Perfectionistic self-presentation in children and adolescents: Development and validation of the Perfectionistic Self-Presentation Scale—Junior Form.
Bibliographic record
Abstract
Research on adults indicates that perfectionistic self-presentation, the interpersonal expression of one's perfection, is associated with a variety of psychopathological outcomes independent of trait perfectionism and Big Five traits. The current article reports on the development and evidence for the validity of the subtest score interpretations of an 18-item self-report measure of perfectionistic self-presentation for children and adolescents. Analyses conducted on data from two clinical samples and one nonclinical sample of children and adolescents found that the Perfectionistic Self-Presentation Scale--Junior Form (PSPS-Jr) reflected a multidimensional model of perfectionistic self-presentation with three subscales: Perfectionistic Self Promotion, Nondisplay of Imperfection, and Nondisclosure of Imperfection. The subscale scores were found to demonstrate internal consistency, and there was good evidence supporting the validity of the interpretation of subscale scores based on this new measure. The subscales were associated with maladaptive outcomes, but were not influenced unduly by biases that included social desirability and differential item functioning by gender. Overall, the PSPS-Jr appears to be a useful measure of the expression of perfection among youths and an important tool in attempting to understand the nature and the consequences of perfectionistic self-presentation in children and adolescents.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".